• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.44-53
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• 2011

This study designed and implemented a web-based computing environment for geovisual analytics using HTML5 canvas. The computing environment supports visualization tools and user's interaction. The visualization tools are cluster map, animated map, temporal parallel coordinate plot, and temporal heat map chart. Users can explore the temporal changes of cluster using multiple view and brushing technique. The computing environment that works well across browsers is used in the computing environment with multiple devices.

• Atmosphere
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• v.15 no.1
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• pp.35-46
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• 2005

Today, the outreach of National Meteorological Service such as PC cluster based Numerical Weather Prediction (NWP) technique is vigorous in the world wide. In this regard, WMO (World Meteorological Organization) asked KMA (Korea Meteorological Administration) to formulate a regional project, which cover most of RA II members, using similar technical system with KMA's. In that sense, Meteorological Research Institute (METRI) in KMA developed Mongolian NWP System (MNWPS) based on PC cluster and transferred the technology to Weather Service Center in Mongolia. The hybrid parallel algorithm and channel bonding technique were adopted to cut cost and showed 41% faster performance than single MPI (Message Passing Interface) approach. The cluster technique of Beowulf type was also adopted for convenient management and saving resources. The Linux based free operating system provide very cost effective solution for operating multi-nodes. Additionally, the GNU software provide many tools, utilities and applications for construction and management of a cluster. A flash flood event happened in Mongolia (2 September 2003) was selected for test run, and MNWPS successfully simulated the event with initial and boundary condition from Global Data Assimilation and Prediction System (GDAPS) of KMA. Now, the cluster based NWP System in Mongolia has been operated for local prediction around the region and provided various auxiliary charts.

• Journal of Internet Computing and Services
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• v.8 no.6
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• pp.43-53
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• 2007

Intrusion detection system(IDS) has recently evolved while combining signature-based detection approach with anomaly detection approach. Although signature-based IDS tools have been commonly used by utilizing machine learning algorithms, they only detect network intrusions with already known patterns, Ideal IDS tools should always keep the signature database of your detection system up-to-date. The system needs to generate the signatures to detect new possible attacks while monitoring and analyzing incoming network data. In this paper, we propose a new outlier cluster detection algorithm with density (or influence) function, Our method assumes that an outlier is a kind of cluster with similar instances instead of a single object in the context of network intrusion, Through extensive experiments using KDD 1999 Cup Intrusion Detection dataset. we show that the proposed method outperform the conventional outlier detection method using Euclidean distance function, specially when attacks occurs frequently.

• Journal of Platform Technology
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• v.6 no.4
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• pp.87-95
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• 2018

With the decrease of sequencing price, many national projects that analyzes 0.1 to 1 million people are now in progress. However, large portion of budget of these large projects is dedicated for construction of the cluster system or purchase servers, due to the lack of programs or systems that can handle large amounts of data simultaneously. In this study, we developed NGSOne, a client program that is easy-to-use for even biologists, and performs SNP analysis using hundreds or more of Whole Genome and Whole Exome analysis without construction of their own server or cluster environment. DRAGEN, BWA / GATK, and Isaac / Strelka2, which are representative SNP analysis tools, were selected and DRAGEN showed the best performance in terms of execution time and number of errors. Also, NGSOne can be extended for various analysis tools as well as SNP analysis tools.

• Journal of Microbiology and Biotechnology
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• v.29 no.5
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• pp.667-686
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• 2019

Streptomyces are attractive microbial cell factories that have industrial capability to produce a wide array of bioactive secondary metabolites. However, the genetic potential of the Streptomyces species has not been fully utilized because most of their secondary metabolite biosynthetic gene clusters (SM-BGCs) are silent under laboratory culture conditions. In an effort to activate SM-BGCs encoded in Streptomyces genomes, synthetic biology has emerged as a robust strategy to understand, design, and engineer the biosynthetic capability of Streptomyces secondary metabolites. In this regard, diverse synthetic biology tools have been developed for Streptomyces species with technical advances in DNA synthesis, sequencing, and editing. Here, we review recent progress in the development of synthetic biology tools for the production of novel secondary metabolites in Streptomyces, including genomic elements and genome engineering tools for Streptomyces, the heterologous gene expression strategy of designed biosynthetic gene clusters in the Streptomyces chassis strain, and future directions to expand diversity of novel secondary metabolites.

• Journal of Animal Science and Technology
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• v.54 no.6
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• pp.463-469
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• 2012

This study utilized a standardization and cluster analysis technique for the selection and classification of beneficial bacteria. A set of synthetic data consisting of 100 individual variables with three characteristics was created for analysis. The three characteristics assigned to each independent variable were designated to have different numeric scales, averages, and standard deviations. The variables were bacterial isolates at random, and the three characteristics were fermentation products, including cell yield, antioxidant activity of culture, and enzyme production. A standardization method utilizing a standard normal distribution equation to record fermentation yields of each isolate was employed to weight their different numeric scales and deviations. Following transformation, the data set was analyzed by cluster analysis. The Manhattan method for dissimilarity matrix construction along with complete linkage technique, an agglomerative method for hierarchical cluster analysis, was employed using statistical computing program R. A total of 100 isolates were classified into groups A, B, and C. In a comparison of the characteristics of each group, all characteristics in groups A and C were higher than those of group B. Isolates displaying higher cell yield were classified as group A, whereas those isolates showing high antioxidant activity and enzyme production were assigned to group C. The results of the cluster analysis can be useful for the classification of numerous isolates and the preparation of an isolation pool using numerical or statistical tools. The present study suggests that a simple technique can be applied to screen and select beneficial microbes using the freely downloadable statistical computing program R.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.415-420
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• 2010

This paper describes the design overview of shared file system $SANique^{TM}$ and analyzes the performance evaluation results of I/O intensive stress test based on various cluster file system architectures. Especially, we illustrate the performance analysis for the comparison results between the $SANique^{TM}$ and the Linux file system EXT3 system that is used to generally in Unix world. In order to perform our evaluation, Oracle 10g database system is operated on the top of cluster file system, and we developed the various kinds of testing tools which are compiled by ESQL/C from Oracle. Three types of architectures are used in this performance evaluation. Those are the cluster file system $SANique^{TM}$, EXT3 and the combined architecture of $SANique^{TM}$ and EXT3. In this paper, we present that the results of $SANique^{TM}$ outperforms other cluster file systems in the overhead for providing the true sharing over the connecting server nodes.

• Women's Health Nursing
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• v.3 no.2
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• pp.208-223
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• 1997

This study was made to suggest the nursing strategies for promoting the behaviors about bone mass health behaviors in order to prevent middle aged women's osteoporosis. This study was a descriptive-correlational design that also concerned to the types which improve bone mass promoting behaviors by inspecting patterns of health locus of control method out of recognizable variables of health improving models influencing on these bone mass promoting behaviors. For these purpose, data were collected by self reported questionnaire in middle school, from 158 women living in Seoul. The measuring tools used in this study about bone mass promoting behaviors and multidimensional health locus of control, were developed by author on the basis of literature review and analyzed by SPSS-PC window, into pearson's correlation, ANOVA, multiple regression, cluster analysis. Data was analyzed as follows. 1. 6 Multidimensional health locus of control scale clusters were existed. : a)cluster I (pure internal), b)cluster II(pure chance), c) cluster III(Believer in control), d), cluster IV(Type VI), e)cluster V(yea sayer), f) cluster VI(nay sayer). There were no findings of the powerful others external cluster and double external cluster. 2. The higher the value of internal health locus of control was, the better the bone mass promoting behaviors were(r=.2891, $p=.00^{**}$). The higher the value of chance external health locus of control was, the worse the bone mass promoting behaviors were(r=-.1367, $p=.00^{**}$). 3. On the basis of these relationships, 6 clusters were significantly different in the bone mass promoting behaviors(F=2.27, $p=.05^*$). The value of bone mass promoting behaviors was ranked the order of type VI>believer in control>pure internal>yea sayer>nay sayer>pure chance external highly. 4. Bone mass promoting behaviors were not significantly different as to age. Suggestion. Based on the results from the study, I would like to make some suggestions as follows. 1) To delay the loss of bone mass in middle aged women, the study on the cluster of the multidimensional health locus of control should be conducted repeatedly. 2) The tool of multidimensional health locus of control should be developed through a qualitative method adjusted on Korean' health culture.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.4
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• pp.27-32
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• 2010

This paper presents an investigation into the pinhead forming process with the objective of finding the optimal forming conditions. In order to this, the orbital forming analysis of a heading MIG was carried out using the explicit finite element method. Relationships between temperature by forming of load and stresses, rake angle by forming final shape and stress distribution were investigated through analysises in order to find an efficient solution. As a result, the higher temperature and orbital rake angle were the better forming conditions.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.928-931
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• 2002

Network based intrusion detection system is a computer network security tool. In this paper, we present an intrusion detection system based on Self-Organizing Maps (SOM) and Resilient Propagation Neural Network (RPROP) for visualizing and classifying intrusion and normal patterns. We introduce a cluster matching equation for finding principal associated components in component planes. We apply data from The Third International Knowledge Discovery and Data Mining Tools Competition (KDD cup'99) for training and testing our prototype. From our experimental results with different network data, our scheme archives more than 90 percent detection rate, and less than 5 percent false alarm rate in one SYN flooding and two port scanning attack types.